Description: A BMW Sedan reportedly made an illegal left turn, causing a minor collision but no injuries with a Cruise autonomous vehicle (AV) operating in autonomous mode.
Entities
View all entitiesAlleged: Cruise developed and deployed an AI system, which harmed Cruise vehicle.
Risk Subdomain
A further 23 subdomains create an accessible and understandable classification of hazards and harms associated with AI
7.3. Lack of capability or robustness
Risk Domain
The Domain Taxonomy of AI Risks classifies risks into seven AI risk domains: (1) Discrimination & toxicity, (2) Privacy & security, (3) Misinformation, (4) Malicious actors & misuse, (5) Human-computer interaction, (6) Socioeconomic & environmental harms, and (7) AI system safety, failures & limitations.
- AI system safety, failures, and limitations
Entity
Which, if any, entity is presented as the main cause of the risk
Human
Timing
The stage in the AI lifecycle at which the risk is presented as occurring
Post-deployment
Intent
Whether the risk is presented as occurring as an expected or unexpected outcome from pursuing a goal
Unintentional
Incident Reports
Reports Timeline

A Cruise autonomous vehicle ("Cruise AV"), operating in driverless autonomous mode, was at a complete stop in response to a red light on southbound Masonic Avenue at the intersection with Oak Street. At the intersection, an Acura Sedan was …

On September 30 last year autonomous driving startup Cruise was granted permission to operate test vehicles in San Francisco without a safety driver behind the wheel.
The approval came with the conditions the vehicles could only be operated…
Variants
A "variant" is an incident that shares the same causative factors, produces similar harms, and involves the same intelligent systems as a known AI incident. Rather than index variants as entirely separate incidents, we list variations of incidents under the first similar incident submitted to the database. Unlike other submission types to the incident database, variants are not required to have reporting in evidence external to the Incident Database. Learn more from the research paper.